Optimal H scaling for sensitivity optimization of detection filters

A. Edelmayer, J. Bokor

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

The paper deals with the sensitivity optimization of detection filters in linear time-varying (LTV) systems which are subject to multiple simultaneous faults and disturbances. The robust fault detection filter design problem as a scaled H filtering problem is considered. The effect of two different input scaling approaches to the optimization process is investigated. The objective is to provide the smallest scaled L2 gain of the unknown input of the system that is guaranteed to be less than a prespecified level, i.e., to produce a filter with optimal disturbance suppression capability in such a way that sufficient sensitivity to failure modes should still be maintained. It is shown how to obtain bounds on the scaled L2 gain by transforming the standard H filtering problem into a convex feasibility problem, specifically, a structured, linear matrix inequality (LMI). Numerical examples demonstrating the effect of the scaled optimization with respect to conventional H filtering is presented.

Original languageEnglish
Pages (from-to)749-760
Number of pages12
JournalInternational Journal of Robust and Nonlinear Control
Volume12
Issue number8
DOIs
Publication statusPublished - Jul 17 2002

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Keywords

  • Constant similarity scaling
  • Convex optimization
  • Fault detection and isolation
  • H filtering
  • LMI optimization
  • LTV systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Chemical Engineering(all)
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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